1. Field of the Invention
The invention generally relates to favorite program recommendations, and more particularly, to automatic favorite program recommendations which keeps track of the viewing habits of users and accordingly generates a list of recommended programs.
2. Description of the Related Art
Analog TV signals may accumulate noises which can not be eliminated during the transmission and processing of signals. Unfortunately, the noises may cause the degression of signal quality and lower user satisfaction. In order to solve this problem, digital TV services are provided due to the advancement in video compression technology. For digital TV services, the analog TV signals are transformed into digital formats via sampling, quantification, encoding, modulation, and other digitalization processes. The current compression standard has been established by the Moving Picture Experts Group 2 (MPEG-2), wherein 1080 horizontal scan lines of High-Definition TV (HDTV) signals may be transmitted in the 6M frequency band used by conventional wireless TVs. The image pictures of the digital TVs possess finer and more photographic features than conventional analog TVs, and the digital TVs provide better audio effect as well.
Additionally, digital signals of digital TV services may include Electronic Program Guide/Electronic Service Guide (EPG/ESG) information other than the video and audio information. With this feature, users may conveniently retrieve the EPG/ESG information to improve TV watching experiences. However, digital TV systems or digital TV software generally just display(s) the received program list on a display for users to look up the programs for today or a few days in the future. It may be time consuming to search for a specific program from the entire program list, especially when there are a great number of TV channels in the program list. Moreover, it may be inconvenient for users to memorize the schedules of all the programs they are interested in. Thus, it is desirable to have an automatic method to keep track of the viewing habits of users and provide recommendations of programs that users may be interested in for reference, and for alleviating the burden of searching for programs from an entire program list.